Data-driven and model-based verification via Bayesian identification and reachability analysis

• Autores: Sofie Haesaert, Paul M.J. Van den Hof, Alessandro Abate
• Localización: Automatica: A journal of IFAC the International Federation of Automatic Control, ISSN 0005-1098, Vol. 79, 2017, págs. 115-126
• Idioma: inglés
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• Resumen

  • Abstract This work develops a measurement-driven and model-based formal verification approach, applicable to dynamical systems with partly unknown dynamics. We provide a new principled method, grounded on Bayesian inference and on reachability analysis respectively, to compute the confidence that a physical system driven by external inputs and accessed under noisy measurements verifies a given property expressed as a temporal logic formula. A case study discusses the bounded- and unbounded-time safety verification of a partly unknown system, encompassed within a class of linear, time-invariant dynamical models with inputs and output measurements.